Context based messaging

ABSTRACT

Systems and methods are provided for monitoring a plurality of chat messages. Values are extracted from multiple chat messages between a first party and a second party. Context is determined for the values and/or messages. The context is used to determine the relationship between the values, messages, and one or more transactions. Once all values of a transaction are identified, an order ticket is generated.

BACKGROUND

Trading of equity, fixed income security, currency, commodity, optionsor futures, has been done in this country since the late 1700s.Traditionally, such trades have occurred on floor-based exchanges, suchas the New York Stock Exchange (NYSE) or the American Stock Exchange(AMEX). The predominant method of trading in these floor-basedenvironments is known as the “open outcry” system, which involves oralcommunications between market professionals at a central location inopen view of other market professionals. In this system, an order istypically relayed out to a trader standing in a “pit.” The trader shoutsout that he has received an order and waits until a broker shouts backcontract terms, and a trading transaction then results. Recently,trading processes have been updated to electronic exchanges ofinformation. One popular method of communication between traders andbrokers is instant messaging (IM) also known as chat messaging.

Chat/IM clients provide a central interface presenting time-orderedmessages from one or more senders, and the user's responses thereto.Current chat clients characterize messages only by the identity of thesender/recipient and the time of creation/receipt. Current chat clientscan recognize quotes on a line-by-line basis, i.e. based on the contentof a single message but only assuming the message contains sufficientinformation. However, where the information relating to a particularquote is spread across multiple messages, which may be interspersedamong other messages, the chat/IM client is unable to determine thecontext of these related messages. Accordingly, there is a need forsystems and methods that can select and identify correctly, values fortransactions from multiple messages using contextual clues.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an illustrative computer network system that may be usedto implement aspects of the disclosed embodiments.

FIG. 2 depicts an illustrative embodiment of a general computer systemfor use with the disclosed embodiments.

FIG. 3 depicts an illustrative example of a chat module of the computernetwork system of FIG. 1.

FIG. 4 depicts an illustrative example of tracking a state of aconversation.

FIG. 5 depicts an example flowchart indicating a method of implementingthe disclosed chat module.

FIG. 6 depicts an example flowchart indicating a method of implementingthe disclosed chat module.

FIG. 7 depicts an example flowchart indicating a method of implementingthe disclosed system for context based messaging.

FIG. 8 depicts an example flowchart indicating a method of implementingthe disclosed system for monitoring and tracking a plurality of chatcommunications.

FIG. 9 depicts an example flowchart indicating a method of implementingthe disclosed system for monitoring a plurality of chat and scoringpotential orders.

FIG. 10 depicts an example flowchart indicating a method of implementingthe disclosed system for monitoring a plurality of chat communications.

DETAILED DESCRIPTION

The disclosed embodiments relate generally to determining context forvalues interspersed among the content of different messages that may becharacterized at most by a sender, a recipient, and a time, the messageshaving subsets of related, but arbitrary content. A context for eachvalue may be determined based on the content of others message, theformat of the values, the personal profiles of the parties involved,prior trades, and/or market data. The context for the values is used toassist in generation of a conversation state that tracks a conversationof interest. When the conversation state approaches or achieves acompleted state, a function may be initiated based on the values storedwithin the conversation state.

Traders and brokers communicate using different forms of communication,sometimes using structured communications, sometimes using naturallanguage or unstructured communication. Instant messaging or Chatmessaging (sometimes referred to as IM or “IMing”) is commonly used tocommunicate between computer users (multi-party or one to one) in apseudo-instantaneous manner. Commercial messenger applications exist andare used frequency such as WhatsApp, Facebook messenger, AIM and WeChat,among others. Proprietary applications exist as well and may besupported and maintained by an exchange or other entity. Suchapplications run on a number of different platforms including personalcomputers (PCs), mobile phones, PDAs or other environments. Chat differsfrom ordinary e-mail in that there is immediacy in the message exchange.Chat makes a continued exchange of messages simpler than sending e-mailback and forth. Chat communications may be text-only or include imagesor moving pictures.

Chat may be used to communicate instructions to a trader who in turnperforms securities trading functions on behalf of clients. It isbeneficial to use chat functions for communicating time-sensitiveinformation as chat is near instantaneous. In order to communicateinstructions, chat systems may use structured messages that encode tradeparameters. A structured message may be composed of ordered values in aspecified sequence or containing values with identifiers. A structuredmessage may be formatted to facilitate processing of the informationcontained within. An example of a structured message may be: “Price=50”.The message contains an identifier “Price=” and a value. Anon-structured message may not contain any identifiers and may becomposed of unstructured information. An example of an unstructuredmessage may be “How about 50?” The unstructured message does not containan identifier to give context to the value 50. In a system that useschat to perform purchases (e.g., in an order management system), chatmessages may be used to place, confirm, and place orders for securities.By adding structure to the chat message, applications such as pricingsystems, risk management systems, order management systems, etc. canreceive and process business critical data contained within the chatmessage because the modified chat message contains structure that may beeasily parsed. Unstructured chat, however, may not be usable as thecontent has no structure and therefore may not be semantically parsed bya computing system. Unstructured chat that spans multiple disparatemessages further complicates encoding trade parameters as there may beno inherent context between values and/or messages. The information thatties the messages together: sender, recipient, and time may beinsufficient on their own to derive a completed trade from a chatmessage.

Certain line by line parsing may be used in chat applications. Whentraders enter trade or quote information, the trade or quote informationmay be translated from a text entry to a data entry that conforms to anynumber of market data formats. However, line by line parsers lack theability to derive context between messages and from unstructuredmessages. Each message must contain every piece of information or theline by line parse will fail to generate a correct transaction. Whenconversations, i.e. multiple interspersed subsets of related messages,about multiple different products take place within the same chatclient, there may be confusion over which values correspond to whichproducts. When a single chat client receives messages from multipledifferent traders related to possibly multiple different products, theredoes not exist a system for distinguishing which messages in a chatenvironment are associated with which products. Further, there does notexist a system that tracks the state of a conversation, updating andreplacing values when contextually implied. Chat/IM clients do notrelate separate message threads or relate together discontinuous subsetsof messages which have some form of relationship. In the example usedabove, a structured message such as “Price=50” is easy to parse. Anunstructured message “How about 50?” may not be parsable by a line byline parser. However, a system that tracks the state of a conversationand uses contextual clues from other messages or sources may be able toderive a context for the message “How about 50?” and extract useableinformation.

Embodiments described herein may extract context from a chat environmentto enable generation of a conversation state. A conversation state maybe generated from values and the context of the values parsed from twoof more messages. The relationships of the values to a conversationstate may be derived from contextual clues and information stored in atrading system. The context or relationship of the values must bedetermined as the values may be arbitrarily spread over differentmessages along with unrelated or conflicting values.

The disclosed embodiments may be implemented to increase the timing andefficiency in the computational system. Interleaved conversationalthreads may be tracked. Values and conversational states may be providedefficiently and accurately without additional user input. The increasedefficiency and decreased usage of resources may lead to additionaltrading, fewer communication errors, and less human error.

One exemplary environment where monitoring and parsing chatcommunications is desirable is in financial markets, and in particular,electronic financial exchanges, such as a futures exchange, such as theChicago Mercantile Exchange Inc. (CME). In particular, an exchange mayoffer multiple products and contracts for purchase that may be enteredinto using the order tickets.

A financial instrument trading system, such as a futures exchange, suchas the Chicago Mercantile Exchange Inc. (CME), provides a contractmarket where financial instruments, e.g., futures and options onfutures, are traded using electronic systems. “Futures” is a term usedto designate all contracts for the purchase or sale of financialinstruments or physical commodities for future delivery or cashsettlement on a commodity futures exchange. A futures contract is alegally binding agreement to buy or sell a commodity at a specifiedprice at a predetermined future time. An option contract is the right,but not the obligation, to sell or buy the underlying instrument (inthis case, a futures contract) at a specified price within a specifiedtime. The commodity to be delivered in fulfillment of the contract, oralternatively the commodity for which the cash market price shalldetermine the final settlement price of the futures contract, is knownas the contract's underlying reference or “underlier.” The terms andconditions of each futures contract are standardized as to thespecification of the contract's underlying reference commodity, thequality of such commodity, quantity, delivery date, and means ofcontract settlement. Cash settlement is a method of settling a futurescontract whereby the parties effect final settlement when the contractexpires by paying/receiving the loss/gain related to the contract incash, rather than by effecting physical sale and purchase of theunderlying reference commodity at a price determined by the futurescontract, price. Options and futures may be based on more generalizedmarket indicators, such as stock indices, interest rates, futurescontracts and other derivatives.

An exchange may provide for a centralized “clearing house” through whichtrades made must be confirmed, matched, and settled each day untiloffset or delivered. The clearing house may be an adjunct to anexchange, and may be an operating division of an exchange, which isresponsible for settling trading accounts, clearing trades, collectingand maintaining performance bond funds, regulating delivery, andreporting trading data. One of the roles of the clearing house is tomitigate credit risk. Clearing is the procedure through which theclearing house becomes buyer to each seller of a futures contract, andseller to each buyer, also referred to as a novation, and assumesresponsibility for protecting buyers and sellers from financial loss dueto breach of contract, by assuring performance on each contract. Aclearing member is a firm qualified to clear trades through the clearinghouse.

The clearing house of an exchange clears, settles and guarantees matchedtransactions in contracts occurring through the facilities of theexchange. In addition, the clearing house establishes and monitorsfinancial requirements for clearing members and conveys certain clearingprivileges in conjunction with the relevant exchange markets.

The clearing house establishes clearing level performance bonds(margins) for all products of the exchange and establishes minimumperformance bond requirements for customers of such products. Aperformance bond, also referred to as a margin requirement, correspondswith the funds that must be deposited by a customer with his or herbroker, by a broker with a clearing member or by a clearing member withthe clearing house, for the purpose of insuring the broker or clearinghouse against loss on open futures or options contracts. This is not apart payment on a purchase. The performance bond helps to ensure thefinancial integrity of brokers, clearing members and the exchange as awhole. The performance bond refers to the minimum dollar depositrequired by the clearing house from clearing members in accordance withtheir positions. Maintenance, or maintenance margin, refers to a sum,usually smaller than the initial performance bond, which must remain ondeposit in the customer's account for any position at all times. Theinitial margin is the total amount of margin per contract required bythe broker when a futures position is opened. A drop in funds below thislevel requires a deposit back to the initial margin levels, i.e., aperformance bond call. If a customer's equity in any futures positiondrops to or under the maintenance level because of adverse price action,the broker must issue a performance bond/margin call to restore thecustomer's equity. A performance bond call, also referred to as a margincall, is a demand for additional funds to bring the customer's accountback up to the initial performance bond level whenever adverse pricemovements cause the account to go below the maintenance.

The exchange derives its financial stability in large part by removingdebt obligations among market participants as they occur. This isaccomplished by determining a settlement price at the close of themarket each day for each contract and marking all open positions to thatprice, referred to as “mark to market.” Every contract is debited orcredited based on that trading session's gains or losses. As prices movefor or against a position, funds flow into and out of the tradingaccount. In the case of the CME, each business day by 6:40 a.m. Chicagotime, based on the mark-to-the-market of all open positions to theprevious trading day's settlement price, the clearing house pays to orcollects cash from each clearing member. This cash flow, known assettlement variation, is performed by CME's settlement banks based oninstructions issued by the clearing house. All payments to andcollections from clearing members are made in “same-day” funds. Inaddition to the 6:40 a.m. settlement, a daily intra-day mark-to-themarket of all open positions, including trades executed during theovernight GLOBEX®, the CME's electronic trading systems, trading sessionand the current day's trades matched before 11:15 a.m., is performedusing current prices. The resulting cash payments are made intra-day forsame day value. In times of extreme price volatility, the clearing househas the authority to perform additional intra-day mark-to-the-marketcalculations on open positions and to call for immediate payment ofsettlement variation. CME's mark-to-the-market settlement system differsfrom the settlement systems implemented by many other financial markets,including the interbank, Treasury securities, over-the-counter foreignexchange and debt, options, and equities markets, where participantsregularly assume credit exposure to each other. In those markets, thefailure of one participant can have a ripple effect on the solvency ofthe other participants. Conversely, CME's mark-to-the-market system doesnot allow losses to accumulate over time or allow a market participantthe opportunity to defer losses associated with market positions.

While the disclosed embodiments may be discussed in relation to futuresand/or options on futures trading, it should be appreciated that thedisclosed embodiments may be applicable to any equity, fixed incomesecurity, currency, commodity, options or futures trading system ormarket now available or later developed. It should be appreciated that atrading environment, such as a futures exchange as described herein,implements one or more economic markets where rights and obligations maybe traded. As such, a trading environment may be characterized by a needto maintain market integrity, transparency, predictability,fair/equitable access and participant expectations with respect thereto.For example, an exchange must respond to inputs, such as trader orders,cancellations, etc., in a manner as expected by the market participants,such as based on market data, e.g., prices, available counter-orders,etc., to provide an expected level of certainty that transactions willoccur in a consistent and predictable manner and without unknown orunascertainable risks. In addition, it should be appreciated thatelectronic trading systems further impose additional expectations anddemands by market participants as to transaction processing speed,latency, capacity and response time, while creating additionalcomplexities relating thereto. Accordingly, as will be described, thedisclosed embodiments may further include functionality to ensure thatthe expectations of market participants are met, e.g., thattransactional integrity and predictable system responses are maintained.

As was discussed above, electronic trading systems ideally attempt tooffer an efficient, fair and balanced market where market prices reflecta true consensus of the value of products traded among the marketparticipants, where the intentional or unintentional influence of anyone market participant is minimized if not eliminated, and where unfairor inequitable advantages with respect to information access areminimized if not eliminated.

Although described below in connection with examples involvinginstruments having multiple components, such as calendar and butterflyspread instruments, the methods described herein are well suited fordetermining final values for any variety of objects conforming to a setof rules or relationships.

Generally, the disclosed embodiments may be applicable to any computerprocessing system that is constrained by a variety of rules and datavalues. When a computer processor attempts to compute a large number ofdata sets in an environment including rules constraints and dataconstraints, the number of possible solutions or combinations of valuescan become unwieldy. The disclosed embodiments allow for the computerprocessing system to accurately parse and efficiently provide ordertickets to users. The disclosed embodiments allow for greater efficiencyfor end users, less processing time spent on parsing, and quickergeneration of orders allowing the market to function efficiency.

The disclosed embodiments may be applicable to contracts for any type ofunderlier, commodity, equity, option, or futures trading system ormarket now available or later developed. The disclosed embodiments arealso not limited to intra-market spread instruments, and accordingly mayalso be used in connection with inter-market spread instruments forcontracts associated with different commodities.

While the disclosed embodiments may be described in reference to theCME, it should be appreciated that these embodiments are applicable toany exchange. Such other exchanges may include a clearing house that,like the CME clearing house, clears, settles and guarantees all matchedtransactions in contracts of the exchange occurring through itsfacilities. In addition, such clearing houses establish and monitorfinancial requirements for clearing members and convey certain clearingprivileges in conjunction with the relevant exchange markets.

The disclosed embodiments are also not limited to uses by a clearinghouse or exchange for purposes of generating an order ticket. Thedisclosed embodiments, may be used for monitoring multiple messages andbuilding a transaction or function based on information included withina set of separate messages.

The methods and systems described herein may be integrated or otherwisecombined with various risk management methods and systems, such as therisk management methods and systems described in U.S. Pat. No. 7,769,667entitled “System and Method for Activity Based Margining” (the '667patent”), the entire disclosure of which is incorporated by referenceherein and relied upon. For example, the methods and systems describedherein may be configured as a component or module of the risk managementsystems described in the above-referenced patent. Alternatively, oradditionally, the disclosed methods may generate data to be provided tothe systems described in the above-referenced patent. For example, thesettlement prices determined by the disclosed embodiments may beincorporated into margin requirement(s) determined by the riskmanagement method or system.

In one embodiment, the disclosed methods and systems are integrated orotherwise combined with the risk management system implemented by CMEcalled Standard Portfolio Analysis of Risk™ (SPAN®). The SPAN systembases performance bond requirements on the overall risk of theportfolios using parameters as determined by CME's Board of Directors,and thus represents a significant improvement over other performancebond systems, most notably those that are “strategy-based” or“delta-based.” Further details regarding SPAN are set forth in the '667patent.

The embodiments may be described in terms of a distributed computingsystem. The particular examples identify a specific set of componentsuseful in a futures and options exchange. However, many of thecomponents and inventive features are readily adapted to otherelectronic trading environments. The specific examples described hereinmay teach specific protocols and/or interfaces, although it should beunderstood that the principles involved may be extended to, or appliedin, other protocols and interfaces.

It should be appreciated that the plurality of entities utilizing orinvolved with the disclosed embodiments, e.g., the market participants,may be referred to by other nomenclature reflecting the role that theparticular entity is performing with respect to the disclosedembodiments and that a given entity may perform more than one roledepending upon the implementation and the nature of the particulartransaction being undertaken, as well as the entity's contractual and/orlegal relationship with another market participant and/or the exchange.

An exemplary trading network environment for implementing tradingsystems and methods is shown in FIG. 1. An exchange computer system 100receives messages that include orders and transmits market data relatedto orders and trades to users, such as via wide area network 126 and/orlocal area network 124 and computer devices 114, 116, 118, 120 and 122,as will be described below, coupled with the exchange computer system100.

Herein, the phrase “coupled with” is defined to mean directly connectedto or indirectly connected through one or more intermediate components.Such intermediate components may include both hardware and softwarebased components. Further, to clarify the use in the pending claims andto hereby provide notice to the public, the phrases “at least one of<A>, <B>, . . . and <N>” or “at least one of <A>, <B>, . . . <N>, orcombinations thereof” are defined by the Applicant in the broadestsense, superseding any other implied definitions here before orhereinafter unless expressly asserted by the Applicant to the contrary,to mean one or more elements selected from the group comprising A, B, .. . and N, that is to say, any combination of one or more of theelements A, B, . . . or N including any one element alone or incombination with one or more of the other elements which may alsoinclude, in combination, additional elements not listed.

The exchange computer system 100 may be implemented with one or moremainframe, desktop or other computers, such as the example computer 200described below with respect to FIG. 2. A user database 102 may beprovided which includes information identifying traders and other usersof exchange computer system 100, such as account numbers or identifiers,user names and passwords. An account data module 104 may be providedwhich may process account information that may be used during trades.

A match engine module 106 may be included to match bid and offer pricesand may be implemented with software that executes one or morealgorithms for matching bids and offers. A trade database 108 may beincluded to store information identifying trades and descriptions oftrades. In particular, a trade database may store informationidentifying the time that a trade took place and the contract price. Anorder book module 110 may be included to compute or otherwise determinecurrent bid and offer prices, e.g., in a continuous auction market, oralso operate as an order accumulation buffer for a batch auction market.A market data module 112 may be included to collect market data andprepare the data for transmission to users.

A risk management module 134 may be included to compute and determine auser's risk utilization in relation to the user's defined riskthresholds. The risk management module 134 may also be configured todetermine risk assessments or exposure levels in connection withpositions held by a market participant.

The risk management module 134 may be configured to administer, manageor maintain one or more margining mechanisms implemented by the exchangecomputer system 100. Such administration, management or maintenance mayinclude managing a number of database records reflective of marginaccounts of the market participants. In some embodiments, the riskmanagement module 134 implements one or more aspects of the disclosedembodiments, including, for instance, principal component analysis (PCA)based margining, in connection with interest rate swap (IRS) portfolios,as described below.

An order processing module 136 may be included to decompose delta-based,spread instrument, bulk and other types of composite orders forprocessing by the order book module 110 and/or the match engine module106. The order processing module 136 may also be used to implement oneor more procedures related to clearing an order.

A settlement module 140 (or settlement processor or other paymentprocessor) may be included to provide one or more functions related tosettling or otherwise administering transactions cleared by theexchange. Settlement module 140 of the exchange computer system 100 mayimplement one or more settlement price determination techniques.Settlement-related functions need not be limited to actions or eventsoccurring at the end of a contract term. For instance, in someembodiments, settlement-related functions may include or involve dailyor other mark to market settlements for margining purposes. In somecases, the settlement module 140 may be configured to communicate withthe trade database 108 (or the memory(ies) on which the trade database108 is stored) and/or to determine a payment amount based on a spotprice, the price of the futures contract or other financial instrument,or other price data, at various times. The determination may be made atone or more points in time during the term of the financial instrumentin connection with a margining mechanism. For example, the settlementmodule 140 may be used to determine a mark to market amount on a dailybasis during the term of the financial instrument. Such determinationsmay also be made on a settlement date for the financial instrument forthe purposes of final settlement.

In some embodiments, the settlement module 140 may be integrated to anydesired extent with one or more of the other modules or processors ofthe exchange computer system 100. For example, the settlement module 140and the risk management module 134 may be integrated to any desiredextent. In some cases, one or more margining procedures or other aspectsof the margining mechanism(s) may be implemented by the settlementmodule 140.

A chat module 142 may be included to provide one or more functionrelating to monitoring and parsing communications between parties. Thechat module 142 may generate order tickets from parsed communications.The chat module 142 may be configured to parse communications. The chatmodule 142 may monitor communications directly or indirectly. The chatmodule 142 may reside on the exchange or be a part of the chatapplication located at each client installation. The chat module 142 maybe implement at the server of a chat service provider. The chat module142 may be connected to the exchange over a network.

One skilled in the art will appreciate that one or more modulesdescribed herein may be implemented using, among other things, atangible computer-readable medium comprising computer-executableinstructions (e.g., executable software code). Alternatively, modulesmay be implemented as software code, firmware code, specificallyconfigured hardware or processors, and/or a combination of theaforementioned. For example, the modules may be embodied as part of anexchange 100 for financial instruments. It should be appreciated thedisclosed embodiments may be implemented as a different or separatemodule of the exchange computer system 100, or a separate computersystem coupled with the exchange computer system 100 so as to haveaccess to margin account record, pricing, and/or other data. Asdescribed above, the disclosed embodiments may be implemented as acentrally accessible system or as a distributed system, e.g., where someof the disclosed functions are performed by the computer systems of themarket participants.

The trading network environment shown in FIG. 1 includes exemplarycomputer devices 114, 116, 118, 120 and 122 which depict differentexemplary methods or media by which a computer device may be coupledwith the exchange computer system 100 or by which a user maycommunicate, e.g., send and receive, trade or other informationtherewith. It should be appreciated that the types of computer devicesdeployed by traders and the methods and media by which they communicatewith the exchange computer system 100 is implementation dependent andmay vary and that not all of the depicted computer devices and/ormeans/media of communication may be used and that other computer devicesand/or means/media of communications, now available or later developedmay be used. Each computer device, which may comprise a computer 200described in more detail below with respect to FIG. 2, may include acentral processor, specifically configured or otherwise, that controlsthe overall operation of the computer and a system bus that connects thecentral processor to one or more conventional components, such as anetwork card or modem. Each computer device may also include a varietyof interface units and drives for reading and writing data or files andcommunicating with other computer devices and with the exchange computersystem 100. Depending on the type of computer device, a user caninteract with the computer with a keyboard, pointing device, microphone,pen device or other input device now available or later developed.

An exemplary computer device 114 is shown directly connected to exchangecomputer system 100, such as via a T1 line, a common local area network(LAN) or other wired and/or wireless medium for connecting computerdevices, such as the network 220 shown in FIG. 2 and described belowwith respect thereto. The exemplary computer device 114 is further shownconnected to a radio 132. The user of radio 132, which may include acellular telephone, smart phone, or other wireless proprietary and/ornon-proprietary device, may be a trader or exchange employee. The radiouser may transmit orders or other information to the exemplary computerdevice 114 or a user thereof. The user of the exemplary computer device114, or the exemplary computer device 114 alone and/or autonomously, maythen transmit the trade or other information to the exchange computersystem 100.

Exemplary computer devices 116 and 118 are coupled with a local areanetwork (“LAN”) 124 which may be configured in one or more of thewell-known LAN topologies, e.g., star, daisy chain, etc., and may use avariety of different protocols, such as Ethernet, TCP/IP, etc. Theexemplary computer devices 116 and 118 may communicate with each otherand with other computer and other devices which are coupled with the LAN124. Computer and other devices may be coupled with the LAN 124 viatwisted pair wires, coaxial cable, fiber optics or other wired orwireless media. As shown in FIG. 1, an exemplary wireless personaldigital assistant device (“PDA”) 122, such as a mobile telephone, tabletbased compute device, or other wireless device, may communicate with theLAN 124 and/or the Internet 126 via radio waves, such as via Wi-Fi,Bluetooth and/or a cellular telephone based data communicationsprotocol. PDA 122 may also communicate with exchange computer system 100via a conventional wireless hub 128.

FIG. 1 also shows the LAN 124 coupled with a wide area network (“WAN”)126 which may be comprised of one or more public or private wired orwireless networks. In one embodiment, the WAN 126 includes the Internet126. The LAN 124 may include a router to connect LAN 124 to the Internet126. Exemplary computer device 120 is shown coupled directly to theInternet 126, such as via a modem, DSL line, satellite dish or any otherdevice for connecting a computer device to the Internet 126 via aservice provider therefore as is known. LAN 124 and/or WAN 126 may bethe same as the network 220 shown in FIG. 2 and described below withrespect thereto.

Users of the exchange computer system 100 may include one or more marketmakers 130 which may maintain a market by providing constant bid andoffer prices for a derivative or security to the exchange computersystem 100, such as via one of the exemplary computer devices depicted.The exchange computer system 100 may also exchange information withother match or trade engines, such as trade engine 138. One skilled inthe art will appreciate that numerous additional computers and systemsmay be coupled to exchange computer system 100. Such computers andsystems may include clearing, regulatory and fee systems.

The operations of computer devices and systems shown in FIG. 1 may becontrolled by computer-executable instructions stored on anon-transitory computer-readable medium. For example, the exemplarycomputer device 116 may store computer-executable instructions forreceiving order information from a user, transmitting that orderinformation to exchange computer system 100 in electronic messages,extracting the order information from the electronic messages, executingactions relating to the messages, and/or calculating values fromcharacteristics of the extracted order to facilitate matching orders andexecuting trades. In another example, the exemplary computer device 118may include computer-executable instructions for receiving market datafrom exchange computer system 100 and displaying that information to auser. In another example, the exemplary computer device 118 may includea non-transitory computer-readable medium that stores instructions forpredicting and/or publishing a current response time or current matchengine latency as described herein.

Numerous additional servers, computers, handheld devices, personaldigital assistants, telephones and other devices may also be connectedto exchange computer system 100. Moreover, one skilled in the art willappreciate that the topology shown in FIG. 1 is merely an example andthat the components shown in FIG. 1 may include other components notshown and be connected by numerous alternative topologies.

Referring to FIG. 2, an illustrative embodiment of a general computersystem 200 is shown. The computer system 200 can include a set ofinstructions that can be executed to cause the computer system 200 toperform any one or more of the methods or computer based functionsdisclosed herein. The computer system 200 may operate as a standalonedevice or may be connected, e.g., using a network, to other computersystems or peripheral devices. Any of the components discussed above,such as the processor 202, may be a computer system 200 or a componentin the computer system 200. The computer system 200 may be specificallyconfigured to implement a match engine, margin processing, payment orclearing function on behalf of an exchange, such as the ChicagoMercantile Exchange, of which the disclosed embodiments are a componentthereof.

In a networked deployment, the computer system 200 may operate in thecapacity of a server or as a client user computer in a client-serveruser network environment, or as a peer computer system in a peer-to-peer(or distributed) network environment. The computer system 200 can alsobe implemented as or incorporated into various devices, such as apersonal computer (PC), a tablet PC, a set-top box (STB), a personaldigital assistant (PDA), a mobile device, a palmtop computer, a laptopcomputer, a desktop computer, a communications device, a wirelesstelephone, a land-line telephone, a control system, a camera, a scanner,a facsimile machine, a printer, a pager, a personal trusted device, aweb appliance, a network router, switch or bridge, or any other machinecapable of executing a set of instructions (sequential or otherwise)that specify actions to be taken by that machine. In a particularembodiment, the computer system 200 can be implemented using electronicdevices that provide voice, video or data communication. Further, whilea single computer system 200 is illustrated, the term “system” shallalso be taken to include any collection of systems or sub-systems thatindividually or jointly execute a set, or multiple sets, of instructionsto perform one or more computer functions.

As illustrated in FIG. 2, the computer system 200 may include aprocessor 202, e.g., a central processing unit (CPU), a graphicsprocessing unit (GPU), or both. The processor 202 may be a component ina variety of systems. For example, the processor 202 may be part of astandard personal computer or a workstation. The processor 202 may beone or more general processors, digital signal processors, specificallyconfigured processors, application specific integrated circuits, fieldprogrammable gate arrays, servers, networks, digital circuits, analogcircuits, combinations thereof, or other now known or later developeddevices for analyzing and processing data. The processor 202 mayimplement a software program, such as code generated manually (i.e.,programmed).

The computer system 200 may include a memory 204 that can communicatevia a bus 208. The memory 204 may be a main memory, a static memory, ora dynamic memory. The memory 204 may include, but is not limited to,computer readable storage media such as various types of volatile andnon-volatile storage media, including but not limited to random accessmemory, read-only memory, programmable read-only memory, electricallyprogrammable read-only memory, electrically erasable read-only memory,flash memory, magnetic tape or disk, optical media and the like. In oneembodiment, the memory 204 includes a cache or random access memory forthe processor 202. In alternative embodiments, the memory 204 isseparate from the processor 202, such as a cache memory of a processor,the system memory, or other memory. The memory 204 may be an externalstorage device or database for storing data. Examples include a harddrive, compact disc (“CD”), digital video disc (“DVD”), memory card,memory stick, floppy disc, universal serial bus (“USB”) memory device,or any other device operative to store data. The memory 204 is operableto store instructions executable by the processor 202. The functions,acts or tasks illustrated in the figures or described herein may beperformed by the programmed processor 202 executing the instructions 212stored in the memory 204. The functions, acts or tasks are independentof the particular type of instructions set, storage media, processor orprocessing strategy and may be performed by software, hardware,integrated circuits, firmware, micro-code and the like, operating aloneor in combination. Likewise, processing strategies may includemultiprocessing, multitasking, parallel processing and the like.

As shown, the computer system 200 may further include a display unit214, such as a liquid crystal display (LCD), an organic light emittingdiode (OLED), a flat panel display, a solid state display, a cathode raytube (CRT), a projector, a printer or other now known or later developeddisplay device for outputting determined information. The display 214may act as an interface for the user to see the functioning of theprocessor 202, or specifically as an interface with the software storedin the memory 204 or in the drive unit 206.

Additionally, the computer system 200 may include an input device 216configured to allow a user to interact with any of the components ofsystem 200. The input device 216 may be a number pad, a keyboard, or acursor control device, such as a mouse, or a joystick, touch screendisplay, remote control or any other device operative to interact withthe system 200.

In a particular embodiment, as depicted in FIG. 2, the computer system200 may also include a disk or optical drive unit 206. The disk driveunit 206 may include a computer-readable medium 210 in which one or moresets of instructions 212, e.g., software, can be embedded. Further, theinstructions 212 may embody one or more of the methods or logic asdescribed herein. In a particular embodiment, the instructions 212 mayreside completely, or at least partially, within the memory 204 and/orwithin the processor 202 during execution by the computer system 200.The memory 204 and the processor 202 also may include computer-readablemedia as discussed above.

The present disclosure contemplates a computer-readable medium thatincludes instructions 212 or receives and executes instructions 212responsive to a propagated signal, so that a device connected to anetwork 220 can communicate voice, video, audio, images or any otherdata over the network 220. Further, the instructions 212 may betransmitted or received over the network 220 via a communicationinterface 218. The communication interface 218 may be a part of theprocessor 202 or may be a separate component. The communicationinterface 218 may be created in software or may be a physical connectionin hardware. The communication interface 218 is configured to connectwith a network 220, external media, the display 214, or any othercomponents in system 200, or combinations thereof. The connection withthe network 220 may be a physical connection, such as a wired Ethernetconnection or may be established wirelessly as discussed below.Likewise, the additional connections with other components of the system200 may be physical connections or may be established wirelessly.

The network 220 may include wired networks, wireless networks, orcombinations thereof. The wireless network may be a cellular telephonenetwork, an 802.11, 802.16, 802.20, or WiMax network. Further, thenetwork 220 may be a public network, such as the Internet, a privatenetwork, such as an intranet, or combinations thereof, and may utilize avariety of networking protocols now available or later developedincluding, but not limited to, TCP/IP based networking protocols.

Embodiments of the subject matter and the functional operationsdescribed in this specification may be implemented in digital electroniccircuitry, or in computer software, firmware, or hardware, including thestructures disclosed in this specification and their structuralequivalents, or in combinations of one or more of them. Embodiments ofthe subject matter described in this specification can be implemented asone or more computer program products, i.e., one or more modules ofcomputer program instructions encoded on a computer readable medium forexecution by, or to control the operation of, data processing apparatus.While the computer-readable medium is shown to be a single medium, theterm “computer-readable medium” includes a single medium or multiplemedia, such as a centralized or distributed database, and/or associatedcaches and servers that store one or more sets of instructions. The term“computer-readable medium” shall also include any medium that is capableof storing, encoding or carrying a set of instructions for execution bya processor or that cause a computer system to perform any one or moreof the methods or operations disclosed herein. The computer readablemedium can be a machine-readable storage device, a machine-readablestorage substrate, a memory device, or a combination of one or more ofthem. The term “data processing apparatus” encompasses all apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, or multiple processors or computers.The apparatus can include, in addition to hardware, code that creates anexecution environment for the computer program in question, e.g., codethat constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, or a combination of one or moreof them.

In a particular non-limiting, exemplary embodiment, thecomputer-readable medium can include a solid-state memory such as amemory card or other package that houses one or more non-volatileread-only memories. Further, the computer-readable medium can be arandom access memory or other volatile re-writable memory. Additionally,the computer-readable medium can include a magneto-optical or opticalmedium, such as a disk or tapes or other storage device to capturecarrier wave signals such as a signal communicated over a transmissionmedium. A digital file attachment to an e-mail or other self-containedinformation archive or set of archives may be considered a distributionmedium that is a tangible storage medium. Accordingly, the disclosure isconsidered to include any one or more of a computer-readable medium or adistribution medium and other equivalents and successor media, in whichdata or instructions may be stored.

In an alternative embodiment, dedicated or otherwise specificallyconfigured hardware implementations, such as application specificintegrated circuits, programmable logic arrays and other hardwaredevices, can be constructed to implement one or more of the methodsdescribed herein. Applications that may include the apparatus andsystems of various embodiments can broadly include a variety ofelectronic and computer systems. One or more embodiments describedherein may implement functions using two or more specific interconnectedhardware modules or devices with related control and data signals thatcan be communicated between and through the modules, or as portions ofan application-specific integrated circuit. Accordingly, the presentsystem encompasses software, firmware, and hardware implementations.

In accordance with various embodiments of the present disclosure, themethods described herein may be implemented by software programsexecutable by a computer system. Further, in an exemplary, non-limitedembodiment, implementations can include distributed processing,component/object distributed processing, and parallel processing.Alternatively, virtual computer system processing can be constructed toimplement one or more of the methods or functionality as describedherein.

Although the present specification describes components and functionsthat may be implemented in particular embodiments with reference toparticular standards and protocols, the invention is not limited to suchstandards and protocols. For example, standards for Internet and otherpacket switched network transmission (e.g., TCP/IP, UDP/IP, HTML, HTTP,HTTPS) represent examples of the state of the art. Such standards areperiodically superseded by faster or more efficient equivalents havingessentially the same functions. Accordingly, replacement standards andprotocols having the same or similar functions as those disclosed hereinare considered equivalents thereof.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, and it can bedeployed in any form, including as a standalone program or as a module,component, subroutine, or other unit suitable for use in a computingenvironment. A computer program does not necessarily correspond to afile in a file system. A program can be stored in a portion of a filethat holds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andanyone or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random access memory or both. The essential elements of a computer area processor for performing instructions and one or more memory devicesfor storing instructions and data. Generally, a computer will alsoinclude, or be operatively coupled to receive data from or transfer datato, or both, one or more mass storage devices for storing data, e.g.,magnetic, magneto optical disks, or optical disks. However, a computerneed not have such devices. Moreover, a computer can be embedded inanother device, e.g., a mobile telephone, a personal digital assistant(PDA), a mobile audio player, a Global Positioning System (GPS)receiver, to name just a few. Computer readable media suitable forstoring computer program instructions and data include all forms ofnon-volatile memory, media and memory devices, including by way ofexample semiconductor memory devices, e.g., EPROM, EEPROM, and flashmemory devices; magnetic disks, e.g., internal hard disks or removabledisks; magneto optical disks; and CD ROM and DVD-ROM disks. Theprocessor and the memory can be supplemented by, or incorporated in,special purpose logic circuitry.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a devicehaving a display, e.g., a CRT (cathode ray tube) or LCD (liquid crystaldisplay) monitor, for displaying information to the user and a keyboardand a pointing device, e.g., a mouse or a trackball, by which the usercan provide input to the computer. Other kinds of devices can be used toprovide for interaction with a user as well. Feedback provided to theuser can be any form of sensory feedback, e.g., visual feedback,auditory feedback, or tactile feedback. Input from the user can bereceived in any form, including acoustic, speech, or tactile input.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back end component,e.g., a data server, or that includes a middleware component, e.g., anapplication server, or that includes a front end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back end, middleware, or front end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include a local area network (“LAN”) and a widearea network (“WAN”), e.g., the Internet.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other. Asystem may depend on certain rules, logic, and inter-related objects anddata. In technical and computing environments, a system may calculatevalues for multiple objects subject to rules, e.g., business orenvironment logic, associated with the objects. Certain object types mayalso depend on other object types.

FIG. 3 depicts an illustrative embodiment of a chat module 142. FIG. 3includes a chat monitor 31, a context module 33, a conversationsprocessor 35, and a message parser 37. The chat module 142 may beconnected to systems or machines outside the exchange system. The chatmodule 142 may communicate with users, traders, and brokers outside ofthe exchange system, such as via wide area network 126 and/or local areanetwork 124 and computer devices 114, 116, 118, 120 and 122. The chatmodule 142 may be configured to monitor a chat communication, parse thecommunications, identify context of the values within thecommunications, and generate one or more conversation states relating toa function based on the values and the context of the values. The chatmodule 142 may be implemented in part as an application on one of thecomputer devices 114, 116, 118, 120 and 122. The chat module 142 may bepart of the exchange computer system 100.

The chat monitor 31 may be configured to monitor chat communicationsbetween parties over a network. The message parser 37 may be configuredto parse messages that are monitored by the chat monitor 31. The contextmodule 33 may be configured to receive one or more value from the parsedmessage and identify a context for the values. The context module 33 maybe configured to identify a relationship between a value and a dataelement. The conversation processor 35 is configured to storeconversation states. The conversation processor 35 receives values fromthe context module 33 and using the associated context, assign thevalues to a relevant conversation state. When a conversation statecontains sufficient values, the conversations processor 35 completes theconversation, performs a function, and provides, for example, acompleted order ticket to a user interface for confirmation. Theconversations processor 35 may identify when the conversation containssufficient values and may prompt a user to provide any additionalinformation required to generate a completed order ticket.

The chat monitor 31 may be implemented as a separate component or as oneor more logic components, such as on an FPGA which may include a memoryor reconfigurable component to store logic and a processing component toexecute the stored logic, or as first logic, e.g. computer programlogic, stored in a memory, such as the memory 204 shown in FIG. 2 anddescribed in more detail above with respect thereto, or othernon-transitory computer readable medium, and executable by a processor,such as the processor 202 shown in FIG. 2 and described in more detailabove with respect thereto, to cause the chat monitor 31 to, orotherwise be operative to monitor a plurality of messages.

The message parsing module may be implemented as a separate component oras one or more logic components, such as on an FPGA which may include amemory or reconfigurable component to store logic and a processingcomponent to execute the stored logic, or as first logic, e.g. computerprogram logic, stored in a memory, such as the memory 204 shown in FIG.2 and described in more detail above with respect thereto, or othernon-transitory computer readable medium, and executable by a processor,such as the processor 202 shown in FIG. 2 and described in more detailabove with respect thereto, to cause the message parsing module to, orotherwise be operative to identify from the plurality of messages, oneor more values.

The message parser 37 may use a standard off the shelf or a proprietaryparser. The message parser 37 may only parse a single at a time (e.g. aline by line parser). The message parser 37 may parse and identify asbased on structural (sequence/order, spaces, delineating characters(punctuation, capitalization)), known key words), or grammatical (nouns,verbs) indicators/clues separate components (characters, numbers, andsymbols) of a chat communication. The relationships of each of thecomponents to one another may be stored in memory alongside thecomponents. For example, the location of a component in a message or theorder of the components may be stored.

The context module 33 may be implemented as a separate component or asone or more logic components, such as on an FPGA which may include amemory or reconfigurable component to store logic and a processingcomponent to execute the stored logic, or as first logic, e.g. computerprogram logic, stored in a memory, such as the memory 204 shown in FIG.2 and described in more detail above with respect thereto, or othernon-transitory computer readable medium, and executable by a processor,such as the processor 202 shown in FIG. 2 and described in more detailabove with respect thereto, to cause the context module 33 to, orotherwise be operative to identify context for the one or more values.

The context module 33 may be in communication with one or more databasesof the exchange. The one or more databases, such as a user database, maycontain data that assists the context module 33 in determining arelationship between an identified value and a conversation state. Thecontext module 33 may be configured to determine relationships betweenvalues from separate messages in the plurality of messages. Each messagefrom the plurality of messages may be parsed by the message parsingmodule to generate one or more components (potentially values). Thecontext of the components may then be determined for each component (orvalue). For example, a value in a first message may be related to asecond value in a second message. The context of each value and messageand resulting relationships may be derived from the format of eachmessage, the format of the value, the profiles of the parties involved,market data, and machine learning techniques. The context module 33applies one or more rules to each value and message to determine thecontext. The context module 33 operates statefully, across messages,i.e. the current message and past messages. The context module 33 maytransmit the values and the context to the conversation processer 33.

The conversation processor 35 may be implemented as a separate componentor as one or more logic components, such as on an FPGA which may includea memory or reconfigurable component to store logic and a processingcomponent to execute the stored logic, or as first logic, e.g. computerprogram logic, stored in a memory, such as the memory 204 shown in FIG.2 and described in more detail above with respect thereto, or othernon-transitory computer readable medium, and executable by a processor,such as the processor 202 shown in FIG. 2 and described in more detailabove with respect thereto, to cause the conversation processor 35 to,or otherwise be operative to generate conversation states for theplurality of messages.

The conversation processor 35 may be configured to generate, store, andverify conversation states. A conversation state may be defined as atemplate that specifies particular items (product, price, quantity,side) of related information necessary to enable, programmatically, afunction, such as the placement of an order. The template may includeone or more data structures or one or more data objects. A value foreach of the particular items or data elements may be stored in one ormore data structures (e.g. in separate registers, memories or memorylocations), each data structure corresponding to a conversation. Forexample, the register for product may store a value, a register forprice may store a value, and so on.

In operation, the context module 33 may determine that a message has norelation, e.g. because the participants are different or no or differentidentifiable elements are found, to a prior message. The conversationprocessor 35 may initiate a new conversation state, a new instance ofthe template wherein the relevant message elements are filled in as newrelated values are extracted. The context module 33 may determine thatthe message relates to a prior message, based on the participants and/orbased on an identifiable element of the message. The context module 33may determine that a value relates to the conversation state based onthe context proximate to the value. The context module 33 and/orconversation processer may determine that the message includesadditional message elements to further define the conversation state,e.g. further fill in missing information of the template. Once thetemplate contains all of or a threshold (sufficient) amount of thenecessary information, the conversation processor 35 may initiate anaction, e.g. an order ticket may be presented to a user. Multipletemplate instances may be “in process” at any given time.

FIG. 4 depicts an example of an updating conversation state 46 derivedfrom an instant message conversation. The chat monitor 31 receives thefour messages from the chat message 44 in that respective order at thetime periods T=1, T=2, T=3, and T=4. The first message from Buyer Astates: “Looking for Dec 2/3 CS.” The second message from Seller states52.5@53.5. The third message from the Buyer asks “What is your Delta.”In the fourth message the seller replies “Delta is 45. now market53@54.”

The message parser 37 parses each of the message of the chat messages 44as they are monitored by the chat monitor 31. The context module 33determines the context of each message and the values contained within.As illustrated by FIG. 4, the parser and context module may functiontogether. The parser uses information from the context module toidentify values. The context module uses information from the parser togenerate context. The conversation processor 35 stores the conversationstate 46 as it evolves over the conversation.

As depicted in FIG. 4, the first message is parsed to identify thevalues. The context of the values is determined. The values and contextare entered into a conversation template that stores the conversationstate. After the first message, the conversation state includes theclient is Buyer A (derived from the chat participants), the product isLN (potentially derived from the history or profiles of Buyer A and theSeller), the Term is Dec 2016 (derived from the “Dec” value and imputedto 2016 based on context, e.g. when the message was time stamped andpast orders), the strategy is call spread (derived based on the value inthe message).

The second message 52@53.5 is then parsed and a context is determined.Using the existing information in the conversation template, the contextmodule 33 may be able to determine that 52@53.5 relates to a bid/askrange. The context module 33 may further use market data to identify thecontext.

The third message “what is your delta” does not contain a value but maybe used to determine the context of the fourth message. Since the thirdmessage appears to be a request for information, the contents of thefourth message may contextually be identified as the informationrequested. Here, the fourth message is explicit in stating that “Deltais 45.” Additionally, the fourth message includes a new market value.The conversation state is now Buyer A, Product LN, Term Dec 2016, 2,3Strikes, call spread strategy, with a bid of 53, ask 54 and a delta of45.

The conversation may continue until the conversation template reaches astate that is complete, the conversation template includes sufficientvalues for required data elements. At this point, an action may be takento generate an order ticket including the values.

In certain embodiments, the conversation state 46 may be displayed via agraphic user interface to a user as each of the plurality of messages isreceived. The display of the conversation state 46 may include one ormore fields that a user, using the interface, may fill in manually togenerate a value for a data element rather than await a messagecontaining the particular information.

The system may determine that a message (or value within the message)has no relation to a conversation state, e.g. because the participantsare different or no or different identifiable elements are found, to aprior message and initiate a new conversation state, a new instance ofthe template wherein the relevant message elements are filled in. Or theinvention may determine that the message relates to a prior message,based on the participants and/or based on an identifiable element of themessage, and includes additional message elements to further define theconversation state, e.g. further fill in missing information of thetemplate. Once the template contains all or a threshold amount of thenecessary information, the action may be initiated, e.g. a completedorder ticket may be presented to the user. Multiple template instancesmay be “in process” at any given time involving communications betweenmultiple users.

The conversation processor 35 may be configured to store one or morecombinations of data elements relating to an incomplete template. As theconversation processor 35 receives additional values from the contextmodule 33 that have a relationship to the order ticket, the conversationstate changes to include the additional values. In certain embodiments,the output of the conversation processor 35 is a completed order ticket.The conversation states and template may be related to an incompleteorder ticket, e.g. an order ticket that is missing a value or has anambiguous value for one or more required data elements. Required dataelements may include data elements such as product, price, quantify,side, etc. Alternative data elements may be used or required dependingon the type of action or trade or order ticket.

In certain embodiments, the context module 33 and conversation modulemay communicate with the user database 102, the account data module 104,the trade database 108, the order book module 110, and/or the marketdata module 112. The user database 102, the account data module 104, thetrade database 108, the order book module 110, and/or the market datamodule 112 may include data that may assist in determining a context ofa data element, a value, or a conversation.

The user database 102 may be configured to store data relating to chatparticipants. The user database 102 may, for example contain datarelating to a linguistic style of a user, e.g. what specific words orphrases mean. The account data module 104 may be configured to storedata relating to one or more accounts. The account data module 104, forexample, may include data that identifies what products a user of anaccount trade on. The account data module 104 may additionally includedata specific to an account rather than a single user. The tradedatabase 108 may be configured to store prior trades relating to one ormore data elements or one or more chat participants. The trade database108 may include contextual information such as the last trade betweenthe parties (which product, what strategy, quantity, etc.). Parties mayhave assumed values for certain data elements such as the product, term,or quantity. While these values may not be mentioned during a chat, theymay be assumed based on the history between the parties. Assumptionssuch as a trader only trades in blocks of 100 may be updated as newinformation is received. The order book module 110 and the market datamodule 112 may be configured to store information relating to current orhistorical market data. Both modules may be used to identify ranges ofvalues for data elements.

FIG. 5 depicts an example workflow of the operation of the chat module142 of FIG. 3. The workflow in FIG. 5 may be used to parse a pluralityof communications using contextual clues found in content of themessages and information stored in the user database 102, the accountdata module 104, the trade database 108, the order book module 110,and/or the market data module 112.

At act A10, the chat module 142 monitors communication of messagesbetween a first party and a second party, wherein a subset thereofrelates to one or more transactions, each characterized by a set of dataitems, each of which requires a value. The messages between a firstparty and a second party may include content such as values related toone or more transactions. The one or more values included in the messagemay be indeterminate as to their meaning or relationship to other datavalues. The messages may alternatively or further contain phrases ornatural language.

The chat module 142 may monitor communications for three or more partiesparticipating in a chat. Using, for example, a group chat function,large numbers of parties may participate in a chat. As a result,messages may or may not be directed between a first party and a secondparty, but rather between multiple parties. A request for a quote may beintended by a sender to be seen and responded to by multiple otherparties in the group chat. Each group chat may include an administrator,who may be responsible for adding or removing participants. Differentlevels of permissions may be granted to different participants. Partiesin a group chat may simultaneously chat one on one with another partywhile chatting in the group chat. In the example given above, a requestfor a quote may be sent to the group. The sender may only receivereplies back on a one to one basis. The chat module 142 may monitor eachof the individual chats and groups chats and derive context from both.

At act A20, the chat module 142 receives a first message communicatedbetween the first party and the second party. Messages may include asender, recipient, and a timestamp. The sender, recipient, and timestampinformation may be used to determine a context for any values includedin the first message. The first party or the second party may be thesender of the first message. The first party and/or the second party maybe the recipient of the second message. The first party and second partymay be participants in a group chat include additional parties. Messagestransmitted by any parties to the group chat may be received by allparties. In an example, the first party may send the first message tothe group chat. The first message may be received by all parties to thechat including the second party.

At act A30, the chat module 142 determines whether the first messagecontains a value for at least one of the set of data items of one of theone or more transactions, the first message either not otherwisespecifying which of the data items or which of the one or moretransactions the value is for. For example, the first message may onlycontain a single value without context. The value may be matched withone or more data items based on a format. For example, if the value is anumber, the data item may be a quantity or price. If the value is aseries of characters, the data item may be a product. A parser may parsethe message separate characters, phrases, and values. The message may beparsed based on alternative criteria such as a linguistic databaseincluding common trader or broker phrases.

At act A40, the chat module 142 or parser may extract the value andstore the value in a buffer.

At act A50, the chat module 142 receives prior to or subsequent to thefirst message, a second message communicated between the first party andthe second party. The first party and second party may be participantsin a group chat include additional parties. Messages transmitted by anyparties to the group chat may be received by all parties. In an example,the first party may send the second message to the group chat. Thesecond message may be received by all parties to the chat including thesecond party. The second message may or may not be related to thecontent of the first message. The content of the second message may beparsed similarly to the first message. The parser may identify anyphrases or values in the second message.

At act A60, the chat module 142 determines whether the second messagecomprises data identifying which of the set of data items and/or whichof the one or more transactions, the stored value is a value for, and ifso, identifying the stored value as the value of that particular item ofthe set of data items. Values or phrases parsed from the second messagealong with other external data such as market data, user profiles, priortrades, etc. may be used to determine a context for the first and secondmessages. If for example, the second message includes a value relatingto a product and the first message includes a numeric value, the chatmodule 142 may communicate with a market data module 112 to determine ifthe numeric value might relate to a price of the product.

In certain embodiments, the chat module 142 may generate an order ticketonce all of the values for each of a data items for a transaction havebeen identified and stored in the buffer. Each transaction may requirecertain data items. For example, a simple trade may require partyinformation, product, price, and quantity. The party information may bederived from the chat participants. The product, price, and quantity maybe identified in a chat communication using the workflow describedabove.

In certain embodiments, the chat module 142 may be configured to displaythe order ticket or the contents of the buffer to one or more of thechat participants. In certain embodiments, the chat may involve three ormore parties.

Table one below illustrates an example plurality of messages (stream ofmessages) between a broker and a trader. The context of each of themessage is described below. The context for each message or value may bederived from information from the other messages and information storedin the user database 102, the account data module 104, the tradedatabase 108, the order book module 110, and/or the market data module112.

TABLE 1 1 Broker: (2/10/2016 2:45:46 PM): WTI Z6 45/48 PS vs 4820 22delta. 2 Trader: (2/10/2016 2:46:05 PM): 123-128 3 Broker: (2/10/20162:47:21 PM): 124/125 4 Broker: (2/10/2016 2:48:00 PM): our bid 5 Trader:(2/10/2016 2:48:50 PM): 100 at 5 6 Trader: (2/10/2016 2:49:10 PM):actually 200 at 5 7 Broker: (2/10/2016 2:49:53 PM): 124's trading weleave 471 8 Trader: (2/10/2016 2:50:31 PM): no cares 9 Broker:(2/10/2016 2:51:07 PM): we leave 371 10 Broker: (2/10/2016 2:51:21 PM):all trade 11 Broker: (2/10/2016 2:51:38 PM): 4's and 5's 12 Trader:(2/10/2016 2:51:51 PM): ah ok 13 Trader: (2/10/2016 2:51:53 PM): fair 14Trader: (2/10/2016 2:52:05 PM): I'd still sell 5s

The first message from the broker to the trader states: “WTI Z6 45/48 PSvs 4820 22 delta.” The message may be interpreted as broker asking foreither an IOI (Indication of Interest) or RFQ (Request For Quote) on thepackage, which is a Crude Oil Dec 2016 45/48 strike Put spread whichincludes selling December 2016 crude oil future at a price of $48.20, ona “22 delta” (which means the ratio of futures contracts). A messageparser 37 and context module 33 may be able to identify each value fromthis line. A conversation state may be generated based on the values.

The second message is a reply from the trader to the broker. The secondmessage contains the component “123-128.” Using data from the marketmodule, the values may correspond to the trader's market $1.23 bid, at$1.28 offer. The trader doesn't include the size or quantity. Dependingon the relationship between broker and market maker and using associatedprofiles, there is likely an assumption of a minimum, e.g., 50 up, 100up, etc.

The broker replies with “124/125.” In this message, the broker repliesthat there is a better market out there, as tight as it can be, just1-tick wide, $1.24 bid at $1.25 offer. The broker follows up thismessage with the next line “our bid” indicating that the broker isrepresenting the bid side here, $1.24, though the quantify is stillindeterminable.

In the next message (5), the trader responds, improving the originaloffer from $1.28, by stating that the trader would join the offer at$1.25 with a 100 contracts. A simple message parser 37 may be unable touse this message. The response, “100 at 5” which if evaluated as asingle line is almost meaningless, but using the context that thecurrent best market is $1.24-$1.25, the context module 33 may conclude“100 at 5” is referring to the “$1.25”, or “5” offer.

The trader corrects his previous message by increasing the offer size to200 contracts, so now the trader is offering 200 contracts at $1.25. The100 quantity from the previous message may be overwritten by the newvalue of 200. The 100 value may be stored temporarily to use as contextor in case the conversation reverts to the old value.

In the next message (7), the broker writes “124's trading we leave 471.”The broker may be informing the trader that the bid side ($1.24) isgetting hit. The 471 may refer to the remaining contracts. This value“471” may be indeterminate.

The trader replies “no cares”, generally meaning that the trader doesn'tcare at that level. This message includes no values, but may be used forcontext.

The broker updates that another 100 traded, down to 371 in the nextmessage.

The broker updates again stating that the broker is all complete at$1.24

The broker adds additional information to previous comments stating “4'sand 5's.” Using the context from previous messages, the broker isstating that the market is no longer $1.24-$1.25, that the $1.24 bid washit and all traded, and although it is a bit less clear, that the $1.25offer either sold at the $1.24 level, or faded (went away).

The trader acknowledges the update.

The trader in the final message (14) informs the broker that the $1.25offer of 200 contracts is still good, despite the change in marketstate.

FIG. 6 depicts an example workflow 600 of the operation of the chatmodule 142 of FIG. 3. The workflow in FIG. 6 may be used to parse acommunication such as that in Table 1 using contextual clues found incontent of the messages and information stored in the user database 102,the account data module 104, the trade database 108, the order bookmodule 110, and/or the market data module 112.

At A110, the chat monitor 31, monitors a stream of communications, e.g.two or more chat communications involving a first party and a secondparty. The chat communications may include additional parties. The chatcommunication may take place during a single time period or overmultiple periods. The chat communications may be archived or stored inmemory. Each message may include explicit values (such as message 1 fromtable 1 above) or may include other content, some of which may be usedto derive a context for the values (message 8 above in table 1). Thechat monitor 31 may identify a sender, a recipient, and a timestamp ofeach message.

At A120, the message parser 37 determines if there is a new value in acommunication. Each message may contain one or more components. Thecomponents may include words, phrases, values, images, or symbols. Eachcomponent may be identified by the message parser 37. The message parser37 may use the format of each component to determine if the componentrelates to a data element. A number, for example, may relate to a dataelement such as price or quantity. A word or acronym may relate to aproduct. In certain embodiments, the message parser 37 may not be ableto determine which specific data element the value relates to. Thespecific type of data element may be determined by the context module33.

At A130, the context of the new value is determined by the contextmodule 33. The context for each value may be derived from informationfrom the messages and information stored in the user database 102, theaccount data module 104, the trade database 108, the order book module110, and/or the market data module 112.

At A140, a determination is made if the new value relates to apreviously received value. Based on the context of the value and/ormessage, the new value may be assigned to an existing conversationstate. A conversation template may track the state of a conversation ofinterest. A conversation of interest may be a collection of dataelements that are related to a specific data element or function. Forexample, a conversation of interest may revolve around a potential orderticket for MSFT. Data elements for such a conversation may be theproduct (already known—MSFT), the parties (may be assumed or derivedfrom the participants), the price, and the quantity. The conversationtemplate tracks each of the values received for each of the dataelements over time. When the conversation template reaches a set pointthe values may be outputted as a function such as an order ticket. Eachconversation template may have one or more required data elements inorder to be sufficiently completed. The conversation template mayinclude additional information.

If the new value does not relate to a previously received value, atA150, a new conversation template is generated including the new value.Multiple conversation template may exist in time. A chat communicationmay reference multiple products or potential order tickets. Aconversation template may be generated for each separate conversation ofinterest.

If the new value does relate to a previously received value, at A160,the new value is added to an existing conversation template thatincludes the previously received value. For example, a conversationtemplate may include the product MSFT. A message includes a value thatcontextually may relate to a price of the product MSFT. The value maythen be added to the conversation template, updating the state of theconversation to include the value. The conversation state may nowinclude the product and price. The quantity may not be known at thistime.

At A170, a determination is made if the conversation template iscomplete. Each conversation of interest may require values for certaindata elements to be complete. In the example above, the parties, aproduct, a price, and a quantify may be required. The parties may beidentified (participants in the chat), the product may be identified(MSFT), the price may be identified, however, the quantify is stillmissing. The conversation template has not reached a state to where itis sufficient to generate an order ticket. The chat module 142 may awaitfurther values from the plurality of messages.

If the conversation template is complete, at A180, a transaction may begenerated from the values in the conversation template. Alternativeactions may be taken when the conversation template is complete.Additionally, the chat module 142 may require further input (such as aconfirmation) to generate a completed order ticket.

In certain embodiment, the conversation template may be provided to oneor more of the chat participants. The conversation template (detailingthe state of the conversation), but may displayed inside or outside thechat interface. One or more of the participants may be able to directlyenter values for data elements.

When applied to a financial exchange computer system, the embodimentsdescribed herein may utilize trade related electronic messages such asinstant messages, chat programs, email, or other electronic messages,etc., so as to enact trading activity in an electronic market. Thetrading entity and/or market participant may have one or multipletrading terminals associated with the session. Furthermore, thefinancial instruments may be financial derivative products. Derivativeproducts may include futures contracts, options on futures contracts,futures contracts that are functions of or related to other futurescontracts, swaps, swaptions, or other financial instruments that havetheir price related to or derived from an underlying product, security,commodity, equity, index, or interest rate product. In one embodiment,the orders are for options contracts that belong to a common optionclass. Orders may also be for baskets, quadrants, other combinations offinancial instruments, etc. The option contracts may have a plurality ofstrike prices and/or comprise put and call contracts. As used herein, anexchange 100 includes a place or system that receives and/or executesorders.

It should be appreciated that the disclosed embodiments may use othertypes of messages depending upon the implementation. Further, themessages may comprise one or more data packets, datagrams or othercollection of data formatted, arranged configured and/or packaged in aparticular one or more protocols, e.g., the FIX protocol, TCP/IP,Ethernet, etc., suitable for transmission via a network 214 as wasdescribed, such as the message format and/or protocols described in U.S.Pat. No. 7,831,491 and U.S. Patent Publication No. 2005/0096999 A1, bothof which are incorporated by reference herein in their entireties andrelied upon. Further, the disclosed message management system may beimplemented using an open message standard implementation, such as FIXBinary, FIX/FAST, or by an exchange-provided API.

FIG. 7 depicts a workflow 700 for tracking a conversation state in aplurality of messages as may be implemented with computer devices andcomputer networks, such as those described with respect to FIGS. 1 and2. Embodiments may involve all, more or fewer actions indicated by theblocks of FIG. 7. The actions may be performed in the order or sequenceshown or in a different sequence.

At act 210, a plurality of messages including messages related to aconversation of interest and messages not related to the conversation ofinterest are monitored. The plurality of messages may includecommunications between two or more parties. The conversation of interestmay relate to a potential order or trade. The conversations may includecommunications in a group chat setting. A group chat may involve threeor more parties. Messages in a group chat may be received by allparticipants in the group chat. Each group chat may involve the same ordifferent sets of participants. For example, a group chat may includeparties A, B, C, and D. A second group chat may include parties A, C, D,and E. Parties may be invited to or may leave group chats at any time.Participants in a group chat may possess different rights for differenttasks. Certain participants may not be able to see certain messagesbetween certain parties. Certain participants may not be able to postmessages at certain times. Each participant may message each otherparticipant outside of the group chat. A message sent directly toanother participant may not be seen by other parties.

At act A220, a first data element in a first message of the plurality ofmessages relating to the conversation of interest is identified. Theplurality of messages may include two or more chat messages communicatedincluding a first party and a second party. Chat clients or IMapplications may be commonly used by traders for over the counterfinancial products. The messages communicated may be characterized onlyby an identity of a sender, an identify of one or more recipients, and atimestamp. The content of the communications may further includeelements that relate to a conversation of interest. Each additionalelement may build on the conversation. The state of a conversation maybe defined as a template that specifies particular data elements(product, price, quantity, side) of related information necessary toenable, programmatically, a function, such as the generation andplacement of an order. Each message may relate to one or more differentconversations. For example, a group message from first party maypotentially relate to potential different conversations for each of theparties to the group chat. Depending on the number of participants, asingle message may be potentially related to tens or hundreds ofdifferent conversations. As the data elements and context of the dataelements and message are identified, the number of relevantconversations may be limited.

Each message in the plurality of message may be parsed to identify oneor more data elements (if one exists). Each data element may include avalue. For a data element such as price, the value may be a numericalvalue. For a data element such as product, the value may be a name ofthe product, a ticker symbol or shorthand for the name of the product.The data elements may correspond to fields or objects in a conversation,for example, fields in an order or trade. In an example such asdescribed above in FIG. 4, a single message may recite “Looking for LNDec 2/3 CS.” The message may be parsed in order to identify thecomponents [looking for]—a common phrase that may be used for context;[LN]—potentially a data element that represents a product;[Dec]—potentially a data element that represents a date;[2/3]—potentially a data element related to strikes; and[CS]—potentially a data element relating to a strategy. Depending on themessage parser 37, only the data element may be identified. Certainmessage parser 37 s may go further and identify the type of dataelement. The output of a parse of a message may be a series of valuesthat may or may not be data elements and any information that describeshow each value is used in the single message.

Once a data element (and/or value) has been extracted from a message,the context of the data element and the message may be determined.Relationships may be discerned based on inter-message elementrelationships, e.g. that a value for a data element specified in onemessage is within a range of values specified in another (prior orsubsequent) message. For example, in an environment with multiplethreaded conversations about different products, the system mayrecognize context based on price ranges of the products. A data elementrelating to price with a value of 45.5 by itself lacks context. Thesystem may use previous messages that have established all possibleproducts the price value may relate to. For example, previouslymentioned products may have price ranges of 3.5-10.5, 40.5-50.5, and102.4-120.4. Given these ranges, the system can understand the contextin which a price value of 45.5 exists, and then generate a relationshipbetween that value and a product that has been previously mentioned, andalso amend any previous message contexts.

Inter message contextual clues or relationships may include: where onemessage defines a unique subset of things and a prior/subsequent messagespecifies something which can only be an element of that unique subset;where one message specifies a query and a subsequent message specifies aresponse to that query. Inter-message relationships may be recognizedbased on characteristics of the sender or recipient, such as based onorder history, profile information, or linguistic patterns.

For a group chat message, the different contextual clues may havedifferent meanings for different parties. Each message may be parsed todetermine which of the group chat participants are relevant. Forexample, in a group chat with 10 participants, a message may only relateto 3 of the participants even though each of the 10 may receive themessage.

Each message, taken from a one to one chat or group chat may beindividually analyzed against each other potentially relevant message inorder to identify contextual clues and relationships between values orthe messages.

At act A230, the value of the first data element is stored in aconversation template. The conversation template may require a currentlyunknown value from a second data element in order to enable a function.For example, if the function was to complete an order ticket, theconversation template may require a product, a quantity, and a price tobe sufficient. The system may continue to monitor the plurality ofmessages. Messages may be related to the conversation of interest,related to a different conversation of interest, or not related to anyconversation of interest. Many of the messages may be unrelated chatteror casual conversation.

In certain embodiments, a data element may be overwritten in theconversation template. In an example, a trader may indicate a firstprice. The first price may be rejected by the recipient of the message.The trader may indicate a second price. Both the first price and secondprice are both related to the conversation of interest. However, theconversation of interest may only use one of the prices. In this case,the subsequent second price would overwrite the first price in theconversation state as the first price was an older value. Other methodsmay be used to determine which value is to be stored.

At act A240, a second value in a second message subsequent to the firstmessage is identified. The second message may be from either the firstparty or second party. The second message may be the next subsequentmessage after the first message between the first party and secondparty. There may be messages in between the first and second messages.The in between messages may be parsed similarly to the first and secondmessage. Each message may be parsed to identify data elements andvalues. One or more interpolated message may either not contain any dataelements (for example, the phrase “did you see the Knicks win thechampionship?”) or contain data elements that are related to a differentconversation of interest. Certain messages may include incorrectinformation or have not contextual value.

At act A250, the second value is determined to be related to the firstvalue. For each identified data element or value, a context may bedetermined. The context may relate to one or more ongoing conversations.For example, an identified value that is a pricing data element may berelated to a conversation regarding a product. The context andrelationship of the pricing data element and the conversation may bedetermined using the pricing range of the product and whether or not thevalue of the pricing data element is within that range. Other contextclues may be included in the messages or in the order of the message (orcomponents of the message). For example, if prior messages had requesteda price for the product, the subsequent pricing data element may likelyrelate to the product. The relationship may not be as clear-cut as theremay be several intervening messages or data elements. In an embodiment,the data element may only be included in a conversation if a thresholdcontext is reached. For data elements that do not meet or exceed thethreshold, the data elements may be stored in a new conversation orreevaluated at a later time once additional information has been parsedfrom the message stream. The threshold context may be based on a scoringsystem that takes into account each of the factors used.

The relationship and or context of the messages and data elements may bedetermined by using several factors. These factors may includeformatting, market data, environment, user profiles, and prior trades.

The formatting of the data may include an amount or order of thecharacters and symbols that are included in the value. For example, adata value of [IBM] most likely would indicate a product and not aprice. Whereas a data value of [55.2] may indicate a price. A data valuesuch as 52.5@53.5 may indicate a bid/ask range due to the format andorder of the characters. Each data element of a conversation templatemay have a specific format. Products may be formatted using generallycharacters, terms or dates such as months may have a specific name orformat.

The market data may be used to determine if a data value is related toconversation. For example, a product AB may have had a recent price in arange of 50-55. A data element that has a value of 90 will most likelynot be the price for product AB. If the other factors surround the dataelement suggest that the data is indeed a price, the data element may berelated to a separate conversation. Alternatively, the data element mayindeed be related to the initial conversation, but not as the price, butfor example, as the Delta.

The environment may be used to determine context of a message or dataelement. The environment may include other component or data elements ina message or messages that are proximate. Messages may include plainlanguage pointers that identify the type of subsequent or previous dataelement. The phrase: “the delta is 40” is a clear indication that thevalue 40 represents the delta. Likewise, if a previous message had asked“what is your delta” and the subsequent message just included the value“40”, the value most likely corresponds to the delta.

User profiles may be used to determine the context of a message or dataelement. The user profile information may include data relating to pasttrades, linguistic styles, and prior communications (IM, email, etc.). Auser, for example, may only trade a specific product. A user may use aspecific phrase when discussing price. One user may use the phrase “ok”to have a first meaning. A second user may use the phrase “ok” to meanssomething else. Past trade between parties, past trades for a product,and market data may also be used to determine the context of a messageor data element.

At act A260, the conversation template is completed using the secondvalue for the second data element. In certain embodiments, theconversation template may require values for a third, a fourth, oradditional data elements in order to be sufficient. Differentconversations may require different data elements in order to besufficient. A sufficient conversation template may include sufficientvalues to generate an order.

In certain embodiments, the conversation state may be provided to a useras the conversation moves from state to state. A display interface mayinclude an indicator that displays the current developing state ofactive conversation states or template instances. The display interfacemay display the conversations the system has identified, the elementsthe system has extracted in each conversation and what information isstill missing in order to enable the function, e.g. the order. The usermay be able to select this “indicator” and manually fill in the missinginformation and/or correct any captured information which is not corrector which the user wishes to modify. The display interface may indicatewhen the system is confused or unable to determine a context or elementand request user input to assist.

For example, uncompleted conversation templates may be generated andprovided to the parties prior to being completed. The current state ofthe conversation for example, may be displayed with one or more emptyfields representing a missing value. A user may manually enter in thevalue for the field to complete the conversation or advance to anupdated state.

In an embodiment, an additional trigger may be required to complete theconversation template. Once a template instance/conversation state isfilled in, the system may await a trigger message/element or other useraction to trigger/initiate the action wherein until that trigger isreceived subsequent messages may include elements which augment ormodify previously received data in the template instance.

In an embodiment, an order ticket may be generated from the conversationtemplate. The order ticket may be provided to the parties. The orderticket may be displayed to both parties with a confirmation input. Theorder ticket may be displayed only one party depending on the context ofthe received data elements. For example, a prior message may serve asconfirmation from one party prior to the conversation template beingcompleted. An order ticket may be display inside of a chat interface orin a separate window. The order ticket may include a button to transmitthe order to the order book module.

The order ticket may use a Financial Information eXchange (FIX)protocol. The FIX protocol is a standard for exchange of such types ofinformation in the securities field. Examples of alternative protocolsinclude FIX Binary, FIX/FAST, an exchange-provided API, FIXML (FIXadapted to XML) and FPML. Accordingly, an OMS provides a useful measureof technology-based communication between the various brokers, between abroker and a brokerage, and between a brokerage and other brokerages,the exchanges, etc.

FIG. 8 depicts an example workflow 800 for generating a completed orderticket as may be implemented with computer devices and computernetworks, such as those described with respect to FIGS. 1, 2, and 3.Embodiments may involve all, more or fewer actions indicated by theblocks of FIG. 8. The actions may be performed in the order or sequenceshown or in a different sequence.

At act A310, a first value relating to a first data element is extractedfrom a first message including a first party and second party. The firstmessage may be a one to one message between the first party and thesecond party. The first message may a group chat message wherein thefirst party or the second party generates the message and the firstparty or the second party receives the message. Values may be identifiedfrom one or more parsed components of a message. Each of the componentsmay be identified and compared against known data elements fields.Combinations of words or phrases may be identified. Alternative forms ofcommunication such as emoji, images, movable pictures may be identified.The type of value may be derived by the message parser 37 or by thecontext module 33. The message parser 37 may use simple formatting todetermine what type a value is. The context module 33 may use additionalinformation and the message structure to determine the context. Thecontext may indicate which data element if any the value is related to.The context may further be used to identify how values related to oneanother and how message relate to one another.

The message parser 37 may transmit each of the identified values (alongwith any identification information) to the context module 33. Thecontext module 33 may identify one or more relationships the identifiedvalues have with previously or concurrently received values. An examplemessage as described above may be: “Looking for LN Dec 2/3 CS.” Themessage may be parsed in order to identify the components [looking for],[LN], [Dec], [2/3], and [CS]. The phrase “looking for” generally maymean a request for a quote. LN may be related to any number of phrasesor data elements. Here, because LN follows directly after “looking for”there is an increased possibility that LN relates to a product. Otherinformation such as the trading tendencies or linguistic style of thesender of the message may be used to determine the correct data elementthat the value LN applies to. [Dec] generally relates to the monthDecember. Additional support for this analysis may be based on if LN isa product and if or if not December is a term for LN. The components[2/3] and [CS] may be identified based on the other components in themessage. Additionally, the profile of the sender may be used to identifywhich types of strategies that the sender prefers.

Each of the components may have a different meaning if used in othercircumstances. Additionally, without further information the actualphrase could have a different meaning. Each value may be provisionallyassigned to a data element until the message parser 37 or context module33 can verify the identification. Data values or context from othersubsequent or prior messages may be used to either back up or repudiatehow the values are assigned to data elements. Any values identified maybe transmitted to a conversation processor 35.

At act A320, a potential order is automatically generated that includesthe first value. An order may require certain values to be completed.For example, a simple buy order may require the product name, a price,and a quantity. Each of the values may be received in separate messages.When one of the values is identified by the message parser 37 or contextmodule 33, the conversation processor 35 generates a potential orderusing the value. The other values not known may be left as null. Incertain embodiments, the values may be provisionally entered based onhistorical data or user profile data. For example, a buyer who onlytrades one product may have that field entered into when a seller sendsa price as long as the price meets a determined price range of thecurrent market for the product.

At act A330, a second message between the first party and second partyis identified as relating to the potential order. The second message maybe the next subsequent message after the first message. Alternatively,additional non-related messages may be interspersed between the firstand second messages. The second message includes a second data element.The second message may be parsed to determine one or more components(including values, possibly related to a data element). The one or morecomponents may be transmitted to the context module 33 to determine therelationship of the components and/or message. Using information such asthe format of the components, the environment, user profiles, tradingprofiles, market data, the context module 33 may determine that thesecond message includes components relating to the potential ordergenerated at act A320. Alternatively, the message parser 37 or contextmodule 33 may determine the second message does not contain any relatedvalues or no values at all. If the second message has non-relatedvalues, the conversation processor 35 may attempt to locate a relatedpotential order, or if none are found, generate a new potential order.

At act A340, a second value relating to the second data element isextracted. The second value may be added to the potential order by theconversation processor 35.

At act A350, a third message between the first party and second party isidentified as relating to the potential order. The third message may bethe next subsequent message after the second message. Alternatively,additional non-related messages may be interspersed between the secondand third messages. The third message includes the third data element.The third message may be parsed to determine one or more components(including values, possibly related to a data element). The one or morecomponents may be transmitted to the context module 33 to determine therelationship of the components and/or message. Using information such asthe format of the components, the environment, user profiles, tradingprofiles, market data, the context module 33 may determine that thethird message includes components relating to the potential ordergenerated at act A320. Alternatively, the message parser 37 or contextmodule 33 may determine the third message does not contain any relatedvalues or no values at all. If the third message has non-related values,the conversation processor 35 may attempt to locate a related potentialorder, or if none are found, generate a new potential order.

In certain embodiments, the third message may contain a third valuerelated to the second data element. For example, in a conversation,parties may go back and forth on price. A price value extracted above atact A340 may be overwritten by a newer value.

At act A360, a third value relating to the third data element isextracted. The third value may be added to the potential order by theconversation processor 35.

At act A370, a detailed order is generated based on the potential orderand including values from the first data element, the second dataelement, and the third data element. A detailed order may be referred toas a completed order ticket. A detailed order may include all the valuesrequired to transmit a trade to an exchange or order book. In certainembodiments, act A370 may await a trigger message or other user actionto trigger the order generation. Until the trigger message (such as aconfirmation) is received subsequent messages may include elements whichaugment or modify previously received data in the template instance.

FIG. 9 depicts an example workflow 900 for generating a plurality ofpotential orders from one or more values identified in a plurality ofmessages as may be implemented with computer devices and computernetworks, such as those described with respect to FIGS. 1, 2, and 3.Embodiments may involve all, more or fewer actions indicated by theblocks of FIG. 9. The actions may be performed in the order or sequenceshown or in a different sequence.

At act A410, a first value is identified in a first message between afirst party and a second party. The first value may be related to one ormore data elements. The first message may be a group chat messagebetween multiple parties including the first party and the second party.A group chat message may have one sender but multiple recipients.

At act A420, a first context is generated for the first value. Thecontext of the first value may indicate that the first value relates toa specific data element (for example, price or a product name). Thecontext may also identify how the first value relates to other values inthe plurality of messages and/or the messages. The context of the firstvalue may not be 100% certain. For example, a single number value mayrelate to multiple different data elements. The first context may beused to identify the relevant parties (the first party and the secondparty) out of larger group of parties participating in a group chat.

At act A430, a first plurality of potential orders is generatedincluding the first value. Using the first context, a plurality ofpotential orders may be generated. For example, if the first valuerelates to a product, potential orders that relate to the product may begenerated.

At act A440, a second value is identified in a second message betweenthe first party and the second party. The second value may be related toone or more data elements.

At act A450, a second context is generated for the second message. Thecontext of the second value may indicate that the second value relatesto a specific data element (for example, price or a product name). Thecontext may also identify how the second value relates to other values(such as the first value) and other data elements in the plurality ofmessages and/or the messages. The context of the second value may not be100% certain. For example, a single number value may relate to multipledifferent data elements such as price or quantity.

At act A460, a second plurality of potential order are generated as asubset of the first plurality of potential orders that include thesecond value. For example, if the first value is related to a product,the first plurality of potential orders may be each order that includesthe first value. If, for example, the second value is related to price,then each of the second plurality of potential orders would include boththe product of the first value and the price of the second value. If thecontext of the second value was uncertain, for example, if the secondvalue may relate to either a price or quantity, the second plurality oforders would include all orders with the first value as the product andthe second value as either the price or quantity.

At act A470, the second plurality of potential orders are scored basedon the first and second context. In certain embodiments, the processormay be unable to determine a relationship between values or messageswith certainty. In an embodiment, values from each message may beassigned an affinity score based on the relationship between multiplevalues. The affinity score may be generated using information relatingto the user profiles for each party, past trades, previously receivedvalues, and trader linguistics.

The affinity score may return a binary result; the value is or is notrelated to a previous value. The affinity score may use a scale todescribe the potential relationship between a first value and a secondvalue. The scale, for example, may be from 1 to 100; 1 indicating thatthe first value and second value are not related; 100 indicating thatthe first value and second value are definitely related. The affinityscore may be used to connect multiple values together. Each value mayinclude one or more affinity scores either relating to different valuesor different potential order tickets.

A score may be used to determine the plausibility of one or morepotential orders. For example, two orders may be generated relating to afirst value of a first data element (e.g. MSFT). A second value isidentified from a subsequent message. The second value may be a price ora quantity for the potential order. The contextual data for the firstvalue, the second value, and the messages in the message stream may beused to score each potential order. Both orders, for example, may bepossible, but the potential order using the second value as a price maybe determined to be the intended order.

A score may be used to determine which parties the values may be relatedto. In a group chat, there may be multiple parties exchanging messages.Each message, including the data values may be relevant to multipledifferent potential orders. The score may be used to determine whichpotential orders relate to which parties.

Machine learning may be used to fine tune the decision process insteadof, or alongside using a scoring system. The contextual data for eachvalue may be store with the result; the result, for example,representing a transmitted order ticket. If, for example, the

At act A480, a third plurality of potential order are provided includingpotential orders from the second plurality of potential orders thatscore above a threshold. The threshold may be set to exclude potentialorders that are unlikely. For example, only the highest scoringpotential order may be provided. Alternatively, the top three, or topfive, top 10%, top 50% or other percentage or count may be used.

FIG. 10 depicts an example workflow 1000 for generating a potentialorder from a plurality of messages as may be implemented with computerdevices and computer networks, such as those described with respect toFIG. 1, 2, or 3. Embodiments may involve all, more or fewer actionsindicated by the blocks of FIG. 10. The actions may be performed in theorder or sequence shown or in a different sequence.

At act A510, a first message is received. A plurality of chat messagesmay be monitored. The plurality of chat messages may include two or moremessages between a first party and a second party that relate to aconversation. The chat messages may be message in group chat. A groupchat may include multiple parties including the first party and thesecond party. The two or more messages may be messages transmitted toand received by the multiple parties including the first party and thesecond party. The first party or the second party may be a transmitterof at least one of the two or more messages.

The first message may include a value that relates to a data element.For example, the value may be a number, the data element may be price.The value may be a symbol or phrase; the data element may be a product.

At act A520, a first value for a first data element is identified in thefirst message. Values may be identified by parsing the message and thendetermining the context of the value, the message, or both. The contextmay be determined based on the content of the message, the content ofother messages in the plurality of chat messages, or contextualinformation from information stored in the user database 102, theaccount data module 104, the trade database 108, the order book module110, and/or the market data module 112.

At act A530, a second message in the plurality of messages is identifiedthat includes a second value. The second message may be the nextsubsequent message after the first message. Other messages in theplurality of chat message may be received between the first and secondmessages. The second message may include a value that relates to a dataelement. For example, the value may be a number, the data element may beprice. The value may be a symbol or phrase; the data element may be aproduct.

At act A540, the second value is determined to be related to the firstvalue. The relationship between the first and second values may bedetermined based on the content of the message, the content of othermessages in the plurality of chat messages, or contextual informationfrom information stored in the user database 102, the account datamodule 104, the trade database 108, the order book module 110, and/orthe market data module 112.

At act A550, one or more potential orders are generated using the firstvalue and the second value. The one or more potential orders may beorder tickets for placing an order for a product on an exchange. The oneor more potential orders may be completed order tickets or incompleteorder tickets. The one or more potential orders may be displayed to oneor more users either in the chat interface or in a separate window.

Although some of the examples discussed herein relate to futurescontracts and associated spread instruments, the disclosed embodimentsfor the optimization module may be applicable to options contracts, andin particular, to strike prices options contracts. For example, eachoptions contract may include multiple strike prices, and an exchangesystem may receive multiple values for each strike price for an outrightoptions contract. Moreover, even after the settlement module processesthe received values, the exchange may have the choice of selecting oneof multiple values for the strike prices for the options contracts.Thus, the optimization module may convert or translate each strike pricefor each options contract into a base object. The system may alsoconvert spread instruments between strike prices into composite objects.

The illustrations of the embodiments described herein are intended toprovide a general understanding of the structure of the variousembodiments. The illustrations are not intended to serve as a completedescription of all of the elements and features of apparatus and systemsthat utilize the structures or methods described herein. Many otherembodiments may be apparent to those of skill in the art upon reviewingthe disclosure. Other embodiments may be utilized and derived from thedisclosure, such that structural and logical substitutions and changesmay be made without departing from the scope of the disclosure.Additionally, the illustrations are merely representational and may notbe drawn to scale. Certain proportions within the illustrations may beexaggerated, while other proportions may be minimized. Accordingly, thedisclosure and the figures are to be regarded as illustrative ratherthan restrictive.

While this specification contains many specifics, these should not beconstrued as limitations on the scope of the invention or of what may beclaimed, but rather as descriptions of features specific to particularembodiments of the invention. Certain features that are described inthis specification in the context of separate embodiments can also beimplemented in combination in a single embodiment. Conversely, variousfeatures that are described in the context of a single embodiment canalso be implemented in multiple embodiments separately or in anysuitable sub-combination. Moreover, although features may be describedabove as acting in certain combinations and even initially claimed assuch, one or more features from a claimed combination can in some casesbe excised from the combination, and the claimed combination may bedirected to a sub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings and describedherein in a particular order, this should not be understood as requiringthat such operations be performed in the particular order shown or insequential order, or that all illustrated operations be performed, toachieve desirable results. In certain circumstances, multitasking andparallel processing may be advantageous. Moreover, the separation ofvarious system components in the embodiments described above should notbe understood as requiring such separation in all embodiments, and itshould be understood that the described program components and systemscan generally be integrated together in a single software product orpackaged into multiple software products.

One or more embodiments of the disclosure may be referred to herein,individually and/or collectively, by the term “invention” merely forconvenience and without intending to voluntarily limit the scope of thisapplication to any particular invention or inventive concept. Moreover,although specific embodiments have been illustrated and describedherein, it should be appreciated that any subsequent arrangementdesigned to achieve the same or similar purpose may be substituted forthe specific embodiments shown. This disclosure is intended to cover anyand all subsequent adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent to those of skill in theart upon reviewing the description.

The Abstract of the Disclosure is provided to comply with 37 C.F.R. §1.72(b) and is submitted with the understanding that it will not be usedto interpret or limit the scope or meaning of the claims. In addition,in the foregoing Detailed Description, various features may be groupedtogether or described in a single embodiment for the purpose ofstreamlining the disclosure. This disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter may be directed toless than all of the features of any of the disclosed embodiments. Thus,the following claims are incorporated into the Detailed Description,with each claim standing on its own as defining separately claimedsubject matter.

It is therefore intended that the foregoing detailed description beregarded as illustrative rather than limiting, and that it be understoodthat it is the following claims, including all equivalents, that areintended to define the spirit and scope of this invention.

What is claimed is:
 1. A computer implemented method comprising:monitoring communication of messages between a first party and a secondparty, wherein a subset thereof relates to one or more transactions,each characterized by a set of data items, each of which requires avalue; receiving a first message communicated between the first partyand the second party; determining whether the first message contains avalue for at least one of the set of data items of one of the one ormore transactions, the first message either not otherwise specifyingwhich of the data items or which of the one or more transactions thevalue is for; extracting the value and storing it in a buffer; receivingprior to or subsequent to the first message, a second messagecommunicated between the first party and the second party; anddetermining whether the second message comprises data identifying whichof the set of data items and/or which of the one or more transactions,the stored value is a value for, and if so, identifying the stored valueas the value of that particular item of the set of data items.
 2. Thecomputer implemented method of claim 1, wherein determining whether thefirst message contains a value is based on a formatting of thecharacters of the value.
 3. The computer implemented method of claim 1,further comprising: determining whether all of the values of the set ofdata items for a particular transaction of the one or more transactionshave been extracted and stored in the buffer; and generating theparticular transaction from the values of the set of data items for theparticular transaction.
 4. The computer implemented method of claim 1,wherein the store value is a price value and the second messagecomprises data that identifies a product related to the price value. 5.A computer implemented method comprising: monitoring a plurality ofmessages communicated between a first party and a second party,identifying a first value of a first data element in a first message ofthe plurality of messages relating to a conversation of interest;storing the first value of the first data element in a conversationmemory, the conversation memory requiring both the first value and anunknown value of a second data element to be complete; identifying asecond value for the second data element in a second message subsequentto the first message; determining the second value is related to thefirst value; storing the second value in the conversation memory; andgenerating a transaction from the conversation memory.
 6. The method ofclaim 1, wherein determining the second value is related to the firstvalue comprises: identifying a range of values for the second dataelement that relate to the first value; and determining if the secondvalue is within the range of values.
 7. The method of claim 1, whereindetermining the second value is related to the first value comprises:identifying contextual language proximate to the second value thatrelates to the first message.
 8. The method of claim 1, wherein thedetermination that the second value is related to the first value isbased on market data related to the first value.
 9. The method of claim1, wherein the determination the second value is related to the firstvalue is based on one or more prior transactions between the first partyand second party.
 10. The method of claim 1, further comprising:displaying one or more values stored in the conversation memory in achat interface.
 11. The method of claim 6, further comprising: providingan input to enter the one or more values for the first data element orthe second data element in the chat interface.
 12. A method forgenerating a completed order from a plurality of messages comprising:extracting a first value relating to a first data element from a firstmessage between a first party and second party; generatingautomatically, a potential order that requires values from the firstdata element, a second data element, and a third data element;identifying as relating to the potential order, a second messageincluding the second data element between the first party and secondparty; extracting a second value from the second data element;identifying as relating to the potential order, a third messageincluding the third data element between the first party and the secondparty; extracting a third value from the third data element; andproviding automatically, the completed order based on the potentialorder and including values from the first data element, the second dataelement, and the third data element.
 13. The method of claim 12,identifying as relating to the potential order, a second message,comprises: identifying contextual language in the second message thatrelates to the first message.
 14. The method of claim 12, identifying asrelating to the potential order, a second message, comprises:identifying market data for the first value; and comparing the marketdata to the second data element.
 15. A method for monitoring andtracking a plurality of chat communications, the method comprising:identifying a first value in a first message between a first party and asecond party; generating a first context for the first value; generatinga first plurality of potential orders including the first value;identifying a second value in a second message between the first partyand the second party; generating a second context for the second value;generating a second plurality of potential orders that are a subset ofthe first plurality of potential orders that include the second value;scoring the second plurality of potential orders for plausibility basedon the first context and second context; providing a third plurality ofpotential orders including potential orders from the second plurality ofpotential orders that scored above a threshold plausibility.
 16. Themethod of claim 15, wherein the second context for the second value isbased on market data for the first value.
 17. The method of claim 15,wherein the second context for the second value is based on a pricerange of the first value.
 18. A method for monitoring a plurality ofchat communications, the method comprising: receiving a first messagebetween a first party and a second party; identifying a first value inthe first message; identifying a second message between the first partyand second party that includes a second value; determining that thesecond value is related to the first value; and generating one or morepotential orders based on the first value and the second value.
 19. Themethod of claim 18, wherein determining that the second value is relatedto the first value comprises: identifying a range of values for a seconddata element that relate to the first value; and determining if thesecond value is within the range of values.
 20. The method of claim 18,wherein determining that the second value is related to the first valuecomprises: identifying contextual language proximate to the second valuethat relates to the first message.
 21. A computer system configured toidentify, track, and store in a memory a plurality of values for aplurality of data elements relating to a conversation of interest, thecomputer system comprising: a chat monitor, coupled to the memory,configured to monitor a plurality of messages between a first party anda second party including two or more messages related to theconversation of interest and a plurality of messages not related to theconversation of interest; a message parser, coupled to the chat monitor,configured to identify a first value and a second value of the pluralityof values in the plurality of messages; a context module, coupled to themessage parser, configured to determine that the first value relates toa first data element and that the second value relates to a second dataelement; the context module further configured to determine that thefirst value and second value are related; a conversation processor,coupled to the context module, configured to store the first value ofthe first data element in a conversation template, the conversationtemplate requiring both the first value and an unknown value of thesecond data element to be complete; the conversation processor furtherconfigured to store the second value as the second data element.
 22. Thecomputer system of claim 21, further comprising: a chat interfaceconfigured to display the conversation template.
 23. The computer systemof claim 22, wherein the chat interface is further configured to receivean input of a value of the plurality of values to be stored in theconversation template.
 24. The computer system of claim 22, wherein thechat interface is further configured to receive a confirmation inputrelating to the values in the conversation template.
 25. A computersystem configured to identify, track, and store in a memory a pluralityof values for a plurality of data elements relating to a conversation ofinterest, the computer system comprising: means for monitoring aplurality of messages between a first party and a second party includingtwo or more messages related to the conversation of interest and aplurality of messages not related to the conversation of interest; meansfor identifying a first data element in a first message of the pluralityof messages relating to the conversation of interest; means for storinga first value of the first data element in a conversation template, theconversation template requiring both the first value and an unknownvalue of a second data element to be complete; means for identifying asecond value for the second data element in a second message subsequentto the first message; means for determining the second value is relatedto the first value; means for completing the conversation template usingthe second value of the second data element; and means for generating atransaction from the conversation template.